IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v128y2023i8d10.1007_s11192-023-04777-4.html
   My bibliography  Save this article

Exploring the evolution of interdisciplinary citation network by the colored network motifs: the case of Perovskite Materials

Author

Listed:
  • Qian Yu

    (Wuhan University of Technology)

  • Rui Tao

    (Wuhan University of Technology)

  • Shan Jiang

    (Wuhan University of Technology)

Abstract

The interdisciplinary knowledge integration has become a typical feature in the development of modern science, which has promoted the production of original scientific achievements and major breakthroughs. The interdisciplinary network describes the knowledge transmission between disciplines, and the colored motif is the repeated subgraph in the network, reflecting the basic pattern of interdisciplinary. By assigning different colors to the nodes in the network, this paper introduces the analysis method of colored motifs into interdisciplinary research to explain the formation and evolution mechanism of interdisciplinary network at the meso-scale. We collected a set of datasets from the core database of Web of Science that contains 27,546 articles related to Perovskite Materials published from 2001 to 2021. After constructing interdisciplinary citation network, we further color network nodes according to their different discipline properties, and analyze evolution characteristics of uncolored and colored network motifs. By statistically analyzing the number of published papers and the proportion of interdisciplinary papers, our results show that the interdisciplinary evolution of Perovskite Materials is divided into two stages: the budding period from 2001 to 2014 and the developing period from 2015 to 2021, where the former stage is featured by knowledge integration, and the latter is dominated by knowledge diffusion. After analyzing colored network motifs, we find that increasing disciplinary categories and citations to different disciplinary knowledge will increase disciplinary diversity, but have a significant negative impact on disciplinary cohesion at the same time, where the former can exert greater influence. In addition, with the expansion of interdisciplinary breadth and reduction of disciplinary diffusion, hub nodes are conductive to emerge, thereby enhancing the cohesion of disciplines.

Suggested Citation

  • Qian Yu & Rui Tao & Shan Jiang, 2023. "Exploring the evolution of interdisciplinary citation network by the colored network motifs: the case of Perovskite Materials," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4421-4446, August.
  • Handle: RePEc:spr:scient:v:128:y:2023:i:8:d:10.1007_s11192-023-04777-4
    DOI: 10.1007/s11192-023-04777-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-023-04777-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11192-023-04777-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kavitha Karunan & Hiran H. Lathabai & Thara Prabhakaran, 2017. "Discovering interdisciplinary interactions between two research fields using citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 335-367, October.
    2. Jiming Hu & Yin Zhang, 2017. "Discovering the interdisciplinary nature of Big Data research through social network analysis and visualization," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 91-109, July.
    3. Loet Leydesdorff & Caroline S. Wagner & Lutz Bornmann, 2018. "Betweenness and diversity in journal citation networks as measures of interdisciplinarity—A tribute to Eugene Garfield," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 567-592, February.
    4. Huang, Hung-Chun & Su, Hsin-Ning, 2019. "The innovative fulcrums of technological interdisciplinarity: An analysis of technology fields in patents," Technovation, Elsevier, vol. 84, pages 59-70.
    5. Jason J. Yoo & Gabkyung Seo & Matthew R. Chua & Tae Gwan Park & Yongli Lu & Fabian Rotermund & Young-Ki Kim & Chan Su Moon & Nam Joong Jeon & Juan-Pablo Correa-Baena & Vladimir Bulović & Seong Sik Shi, 2021. "Efficient perovskite solar cells via improved carrier management," Nature, Nature, vol. 590(7847), pages 587-593, February.
    6. Fabio Saracco & Riccardo Di Clemente & Andrea Gabrielli & Tiziano Squartini, 2015. "Detecting early signs of the 2007-2008 crisis in the world trade," Papers 1508.03533, arXiv.org, revised Jul 2016.
    7. Andy Stirling, 2007. "A General Framework for Analysing Diversity in Science, Technology and Society," SPRU Working Paper Series 156, SPRU - Science Policy Research Unit, University of Sussex Business School.
    8. Ismael Rafols & Martin Meyer, 2010. "Diversity and network coherence as indicators of interdisciplinarity: case studies in bionanoscience," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 263-287, February.
    9. Pradeep Kumar Hota & Balaji Subramanian & Gopalakrishnan Narayanamurthy, 2020. "Mapping the Intellectual Structure of Social Entrepreneurship Research: A Citation/Co-citation Analysis," Journal of Business Ethics, Springer, vol. 166(1), pages 89-114, September.
    10. Loet Leydesdorff & Félix Moya-Anegón & Vicente P. Guerrero-Bote, 2015. "Journal maps, interactive overlays, and the measurement of interdisciplinarity on the basis of Scopus data (1996–2012)," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(5), pages 1001-1016, May.
    11. Jiaming Jiang & Rajeev K. Goel & Xingyuan Zhang, 2020. "IPR policies and determinants of membership in Standard Setting Organizations: a social network analysis," Netnomics, Springer, vol. 21(1), pages 129-154, December.
    12. James M. Ball & Annamaria Petrozza, 2016. "Defects in perovskite-halides and their effects in solar cells," Nature Energy, Nature, vol. 1(11), pages 1-13, November.
    13. Leland H. Hartwell & John J. Hopfield & Stanislas Leibler & Andrew W. Murray, 1999. "From molecular to modular cell biology," Nature, Nature, vol. 402(6761), pages 47-52, December.
    14. Elizabeth Gibney, 2017. "2017 sneak peek: What the new year holds for science," Nature, Nature, vol. 541(7635), pages 14-15, January.
    15. Wei, Ye & Jin, Ying & Ma, Dingyu & Xiu, Chunliang, 2021. "Impact of colored motif characteristics on the survivability of passenger airline networks in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhichao Ba & Yujie Cao & Jin Mao & Gang Li, 2019. "A hierarchical approach to analyzing knowledge integration between two fields—a case study on medical informatics and computer science," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1455-1486, June.
    2. Wooseok Jang & Heeyeul Kwon & Yongtae Park & Hakyeon Lee, 2018. "Predicting the degree of interdisciplinarity in academic fields: the case of nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 231-254, July.
    3. Ronald Rousseau, 2018. "The repeat rate: from Hirschman to Stirling," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 645-653, July.
    4. Kim, Hyeyoung & Park, Hyelin & Song, Min, 2022. "Developing a topic-driven method for interdisciplinarity analysis," Journal of Informetrics, Elsevier, vol. 16(2).
    5. Yi Bu & Mengyang Li & Weiye Gu & Win‐bin Huang, 2021. "Topic diversity: A discipline scheme‐free diversity measurement for journals," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(5), pages 523-539, May.
    6. Ricardo Arencibia-Jorge & Rosa Lidia Vega-Almeida & José Luis Jiménez-Andrade & Humberto Carrillo-Calvet, 2022. "Evolutionary stages and multidisciplinary nature of artificial intelligence research," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5139-5158, September.
    7. Alfonso Ávila-Robinson & Cristian Mejia & Shintaro Sengoku, 2021. "Are bibliometric measures consistent with scientists’ perceptions? The case of interdisciplinarity in research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7477-7502, September.
    8. Zhao, Yi & Liu, Lifan & Zhang, Chengzhi, 2022. "Is coronavirus-related research becoming more interdisciplinary? A perspective of co-occurrence analysis and diversity measure of scientific articles," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    9. Loet Leydesdorff, 2018. "Diversity and interdisciplinarity: how can one distinguish and recombine disparity, variety, and balance?," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 2113-2121, September.
    10. Lin Zhang & Beibei Sun & Zaida Chinchilla-Rodríguez & Lixin Chen & Ying Huang, 2018. "Interdisciplinarity and collaboration: on the relationship between disciplinary diversity in departmental affiliations and reference lists," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 271-291, October.
    11. Fan, Yangliu & Lehmann, Sune & Blok, Anders, 2022. "Extracting the interdisciplinary specialty structures in social media data-based research: A clustering-based network approach," Journal of Informetrics, Elsevier, vol. 16(3).
    12. Jingjing Ren & Fang Wang & Minglu Li, 2023. "Dynamics and characteristics of interdisciplinary research in scientific breakthroughs: case studies of Nobel-winning research in the past 120 years," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4383-4419, August.
    13. Loet Leydesdorff & Inga Ivanova, 2021. "The measurement of “interdisciplinarity” and “synergy” in scientific and extra‐scientific collaborations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(4), pages 387-402, April.
    14. Leydesdorff, Loet & Wagner, Caroline S. & Bornmann, Lutz, 2019. "Interdisciplinarity as diversity in citation patterns among journals: Rao-Stirling diversity, relative variety, and the Gini coefficient," Journal of Informetrics, Elsevier, vol. 13(1), pages 255-269.
    15. Stephen Carley & Alan L. Porter, 2012. "A forward diversity index," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 407-427, February.
    16. Lin Zhang & Ronald Rousseau & Wolfgang Glänzel, 2016. "Diversity of references as an indicator of the interdisciplinarity of journals: Taking similarity between subject fields into account," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(5), pages 1257-1265, May.
    17. Diego Chavarro & Puay Tang & Ismael Rafols, 2014. "Interdisciplinarity and research on local issues: evidence from a developing country," Research Evaluation, Oxford University Press, vol. 23(3), pages 195-209.
    18. Su, Hsin-Ning & Moaniba, Igam M., 2017. "Investigating the dynamics of interdisciplinary evolution in technology developments," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 12-23.
    19. Loet Leydesdorff & Dieter Franz Kogler & Bowen Yan, 2017. "Mapping patent classifications: portfolio and statistical analysis, and the comparison of strengths and weaknesses," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1573-1591, September.
    20. Filippo Corsini & Rafael Laurenti & Franziska Meinherz & Francesco Paolo Appio & Luca Mora, 2019. "The Advent of Practice Theories in Research on Sustainable Consumption: Past, Current and Future Directions of the Field," Sustainability, MDPI, vol. 11(2), pages 1-19, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:128:y:2023:i:8:d:10.1007_s11192-023-04777-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.